Prediction of grinding machinability when grind P20 tool steel using water based ZnO nano-coolant

摘要

Grinding is often an important finishing process for many engineering components and for some components is even a major production process. The surface roughness, Ra is also an important factor affecting many manufacturing departments. In this study, a model have been developed to find the effect of grinding condition which is depth of cut, type of wheel and type of grinding coolant on the surface roughness on AISI P20 tool steel and wheel wear. Besides that, the objective of this study is to determine the effect of Zinc Oxide (ZnO) nano-coolant on the grinding surface quality and wheel wear for various axial depth. Precision surface grinding machine is used to grind the AISI P20 tool steel. The work table speed would be constant throughout the experiment which is 200 rpm. The experiment conducted with grinding depth in the range of 5 to 21µm. Besides, Aluminum Oxide wheel and Silicon Carbide wheel are used to grind the work piece in this experimental study. Next, the experiment will conduct using ZnO nano-coolant. Finally, the artificial intelligence model has been developed using ANN. From the result, it shows that the lower surface roughness and wheel wear obtain at the lowest cutting depth which is 5 µm. Besides that, grind using ZnO nano-coolant gives better surface roughness and minimum wheel wears compare to grind using water based coolant. From the prediction of ANN, it shows that the surface roughness became constant after cutting depth 21 µm. In conclusion, grind using ZnO nano-coolant with cutting depth 5 µm obtain a better surface roughness and lowest wheel wear. As a recommendation, various machining can be conducted using ZnO nano-coolant to emphasize better results.